96/12 Rapporter Reports
Knut H. Alfsen, På l Boug and
Dag Kolsrud
Energy demand, carbon
emissions and acid rain
Consequences of a changing Western
Europe
Statistisk sentralbyrå • Statistics Norway
Oslo—Kongsvinger 1996
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Revised since the previous issue
ISBN 82-537-4285-1
ISSN 0806-2056
Emnegruppe
01 Naturressurser og naturmiljo
Emneord
Energiettersporsel
Luftforurensning
Økonomisk vekst
Scenarier
SEEM
Sur nedbor
Vest-Europa
Design: Enzo Finger Design
Trykk: Statistisk sentralbyr6
Symbol
••
•••
-
0
0,0
*
I
r
Abstract
Knut H. Alfsen, Pal Boug and Dag Kolsrud
Energy demand, carbon emissions and acid rain
Consequences of a changing Western Europe
Reports 96/12 • Statistics Norway 1996
Employing a multisector energy demand model of thirteen Western European countries (SEEM) together with the
RAINS model developed by IIASA, we in this report address the question of how much the European economic and
political integration process matter for future development in energy demand, emissions to air of key pollutants and
transboundary transport of sulphur and nitrogen. We do this by comparing two simulation scenarios; one scenario
based on the assumption of further European integration versus another scenario where fragmentation is assumed to
prevail. Both scenarios cover the period from 1991 to 2020. The focus of the report is on consequences for future
demand for fossil fuels, emissions of CO2, SO2 and NO., and transport and deposition of sulphur and nitrogen.
Average annual growth in GDP in the integration scenario is 2.3 per cent, while demand for energy, emissions of CO2,
SO2 and NO., and nitrogen deposition all show average annual growth rates from 1.7 to 1.9 per cent. Deposition of
sulphur grows at the slightly lower rate of 1.4 per cent per year in this scenario. In the fragmentation scenario all
growth rates are reduced by 0.5-0.7 percentage points, except the rate of annual average growth in SO2 emissions
which is reduced by 0.8 percentage point. The results vary considerably, however, over countries, sectors and fuel
types.
Keywords: Energy demand, emissions to air, economic growth, SEEM, acid rain, Western-Europe.
Acknowledgement: This paper is an outcome of the project "Energy scenarios for a changing Europe" carried out
at Statistics Norway in cooperation with ECN, The Netherlands. Financial support from Statoil, The Dutch Ministry of
Planning and The Norwegian Ministry of Environment is acknowledged.
3
Reports 96/12
Energy demand and emissions
Contents
1.
Introduction 2.
The SEEM model 2.1. Model structure 2.2. The sector models 2.3. Model input and output 3.
Integration or fragmentation? A brief description of alternative economic scenarios 3.1. Ongoing Western European Integration (IS) 3.2. Western European Fragmentation (FS) 3.3. Model inputs 3.3.1. Economic growth 3.3.2. Energy prices 3.3.3. Autonomous efficiency improvement 7
8
8
9
10
12
12
13
13
13
14
14
4.1. Energy demand 4.2. Emissions to air 4.2.1. Emission of CO 2 4.2.2. Emission of SO 2 and NO 4.2.3. Deposition of SO 2 and NO 15
15
18
18
19
20
5.
22
4.
Simulation results Conclusion References 23
Appendix: Country tables 24
Previously issued on the subject 25
Recent publications in the series Reports 26
5
Reports 96/12
Energy demand and emissions
1. Introduction
European integration has been on the agenda for a
long time. Whether this momentum towards greater
integration can be kept up also in the next few decades
is however uncertain. The problem addressed in this
report is how this uncertainty might affect its energy
markets and how this in turn could affect emissions of
carbon dioxide (CO2), and emissions, transport and
deposition of the two most important acid compounds;
sulphur dioxide (SO2) and nitrogen oxides (NO.).
European fragmentation, respectively. Simulation
results based on these alternative economic development paths are given in section 4, while section 5
concludes. The appendix contains a set of detailed
country tables covering emissions to air and deposition
of SO2 and NOR.
The strategy followed is first to describe how further
integration or lack of integration (fragmentation) can
affect the economic development of 13 countries in
Western Europe. This description is of an ad hoc nature
and is treated as exogenous input to this analysis.
Based on alternative growth paths, we employ a
Sectoral European Energy Model (SEEM) to calculate
likely impacts on the energy markets, where basically
three types of primary energy goods are treated
endogeneously; gaseous fuels, liquid fuels and solid
fuels1. Supply and demand of electricity based on
thermal power production is also modelled in SEEM.
Other types of energy technologies, e.g. nuclear power
and alternative energy technologies, are treated as
exogenously given. Secondly, based on projected
energy demand, emissions of the greenhouse gas
carbon dioxide (CO2) is calculated by the SEEM
model', while IIASA's RAINS model is utilised in
calculating emissions, atmospheric transport and
deposition of SO2 and NOR. The inputs to the RAINS
model are the energy consumption paths generated by
the SEEM model.
Given this strategy, the rest of the report is organised
as follows. The next section briefly describes the
structure and working of the SEEM model'. Section 3
then comments on the economic assumptions used in
the two scenarios of further European integration and
1 Studies based on a previous version of the model have been
published by Birkelund et al. (1993, 1994) and Alfsen et al. (1995).
2
The topic of CO2 emissions in a changing Europe is discussed in
detail in Boug and Brubakk (1996).
3
The model is documented in detail in Brubakk et al. (1995), Boug
(1995) and Kolsrud (1996).
7
Energy demand and emissions
Reports 96/12
2. The SEEM model
2.1. Model structure
The Sectoral European Energy Model (SEEM)4 is a
simulation model for energy demand projections for 13
countries in Western Europe. The model consists of
separate model blocks for each of the following
countries:
• Four major energy consumers: Germany, France,
United Kingdom, and Italy;
• Four Nordic countries: Denmark, Sweden, Finland
and Norway;
• Five other countries: Spain, the Netherlands,
Belgium, Austria, and Switzerland.
Together, these countries consumed about 90 per cent
of the total energy use in the OECD Europe in 1991.
Neither inter-country trade nor supply of primary
energy is modelled within SEEM. Supply of electric
power is, however, part of the model. In each country
there are five sectors: manufacturing industries and
service industries (hereafter referred to as industry and
services), households, transport' and power production. Energy commodities covered in SEEM are coal,
oil, gas, electricity and various transport fuels. Demands for nuclear and renewable fuels are treated as
given in the model.
The model is partial in the sense that it determines the
demand for energy based on exogenous prices, taxes
and production and consumption activity levels (cf. figure 2.1). Hence, we focus on the demand side of the
energy markets, with the assumption that demand
equals realised consumption. However, both the demand and the supply side of the Electricity generating
sector is included in the model. Cost minimising
behaviour is assumed for all sectors using energy.
The choice of behavioural functional forms and parameters, and the quantitative methodology, were chosen
considering the data and resource limitations.
4
SEEM version 2.0 has been developed in co-operation with the
Netherlands Energy Research Foundation ECN.
5 Fuel demand for transport purposes has been grouped into one
sector.
8
Furthermore, model transparency and the scope for
implementation and simulation on a Personal Computer were important design criteria.
Parameters representing the behaviour of the sectors
included in the model are estimated on empirical data
or calibrated on research results published in international journals. For all estimations and the calibration
of the energy use and prices to the base year (1991),
data from the International Energy Agency (IEA,
1993a, b) were used.
We have formulated the model equations directly at
the sector level by adopting a "top down" modelling
approach. However, the macro-level producer or consumer that we study, is assumed to behave according
to microeconomic considerations. In fact, the neoclassical micro model often seems more meaningful. at
the sector level than at the individual level. In particular, continuous substitution possibilities are perhaps
more realistic at a sectoral level. These substitution
possibilities are premises for cost minimising and utility
maximising behaviour, which are crucial assumptions
when deriving the fuel demand functions.
Figure 2.1 depicts the structure of the model block for
one country. In a first step the model determines the
demand for coal, oil, natural gas and electricity in the
end user sectors, based on exogenous information on
activity levels, income, and technology, in addition to
production factor prices.
In the electricity generation sector the need for domestic production of power is derived, given an exogenous matrix of net power import and a constant
percentage of distribution losses. The electricity
requirements can be produced in several ways: By
thermal power plants using coal, oil or natural gas as
inputs, by nuclear power plants and/or by plants using
renewables (now mainly hydro power).
Reports 96/12
Energy demand and emissions
Figure 2.1. SEEM model structure
Exogenous variables
0 Endogenous variables
Activity
and income
The different technologies' share of the total electricity generation depends on their relative costs of
production. Based on the production costs of electricity, margins and taxes, the model calculates
electricity end-user prices in all sectors. Adding the
use of fossil fuels in the end user sectors to fossil fuel
inputs in thermal power production yields the total
demand for each fossil fuel. In a submodel, demand
for coal, oil and natural gas are converted into
estimates of CO, emissions.
Table 2.1 gives a list of the countries, sectors and
fuels covered by the model together with their model
codes.
2.2. The sector models
Fuel
demand in
power
production
Net power
import and
distribution
losses
Costs of
power produced
by coal, oil,
gas, nuclear
and renewables
In SEEM, the industry sector is described by a twolevel fuel-share model. The upper level determines
the cost minimising combination of the three aggregate production factors; capital, labour and energy,
while the lower level determines the cost minimising
combination of the different fuels included in the
energy aggregate, i.e. the optimal proportion (fuel
shares) of coal, oil, natural gas and electricity. At
both levels Cobb-Douglas production functions have
been used. To allow for sluggish adjustment of capital
input to price changes, demand is lagged according to
a partial adjustment hypothesis. Hicks-neutral technical progress is specified at the upper level. The fuel
demand equations at the lower level are calibrated
using information about the cost shares of the
different fuels. At the upper level the calibration is
based on elasticities found in other studies.
Table 2.1. Model specifications and codes
Stationary sectors
Fuels in mobile sectors
EL
HO
IN
SE
ST
FC
BD
GA
GO
RE
RD
DI
EL
01
Electricity production
Households
Manufacturing industries
Service industries
Stationary consumption (=EL+H0+IN+SE)
Final consumption (=ST-EL)
Mobile sectors
TP
TF
FA
MO
Passengers transport
Freight transport
Air fieight
Mobile consumption (=TP+TF+FA)
Fuels in stationary sectors
NUC
REN
COA
OIL
NGS
ELE
Nuclear fuel
Renewable fuels
Coal
Oil
Natural gas
Electricity
Diesel for buses
Gas
Gasoline
Electricity for rail
Diesel for rail
Diesel
Electricity
Oil
Countries
AU
BE
BR
CH
DK
FR
GB
IT
NL
NO
SF
SP
SW
Austria
Belgium
Germany
Switzerland
Denmark
France
United Kingdom
Italy
The Netherlands
Norway
Finland
Spain
Sweden
9
Energy demand and emissions
For service industries we have estimated a fuel-share
model similar to that of the industry sector by postulating Constant Elasticity of Substitution (CES)
production functions for the energy aggregates. We
allow for a nested model in three levels (compared to
two in the industry sector) for countries with substantial use of all four energy sources, i.e coal, oil, gas and
electricity. At the upper level, electricity and an aggregate of oil, gas and coal are separate inputs. This implies a hypothesis that the use of electricity contributes
to production in a profoundly different way compared
to fossil fuels. While the latter are used for space heating mainly, electricity is mostly used in appliances like
computers and lighting for which energy substitution is
impossible. The energy demand functions at the upper
level are log-linear, with calibrated parameters. At the
intermediate level, the fossil fuel aggregate is produced
by a CES technology utilising an aggregate of oil and
gas, and of solids. At the lower level the oil and gas
aggregate is produced, also by a CES technology. The
intermediate and lower level parameters are estimated.
The household sector model is equal to the services
sector model, except that at the upper level «private
consumption» and «prices of other goods» substitute
for the production activity level and factor costs others
than energy costs as explanatory variables, respectively. Also in the households, electricity and fossil fuel
prices are variables which determine the households'
demand for electricity and fossil fuel aggregate at the
upper level. The modelling and parametrisation of the
lower levels are similar to the service sector model.
The transport sector model is divided into passenger
transport, freight transport, and air transport. Fuel
efficiencies in the transport sectors are based on linear
penetration of new technologies.
Air transport is treated separately because most air
transport is combined passenger and freight transport.
Demand for fuel (kerosene) is modelled as a function
of the price of kerosene and gross domestic production.
For passenger transport both private and public transport are considered; more specifically cars (gasoline,
gasoil and gas), trains (electricity and gasoil) and
busses (diesel) are distinguished. At the upper level of
the passenger transport model total demand for person
kilometres is a function of consumer expenditures and
a transport price index. At the lower level the demand
for transport is split into the different modes in
proportions depending on fuel prices and capital prices
of the respective modes. This determines demand for
person kilometres by transport mode. Given figures for
car occupancy and efficiency, the corresponding fuel
use is then computed.
The freight transport is modelled at the upper level by
assuming that the development of domestic production
determines total demand for tonnes kilometres. Given
10
Reports 96/12
exogenous assumptions on mode shares and fuel
efficiency, the demand for the different fuels are then
calculated.
In the electricity generation model the domestic power
production requirements are determined by adding end
user electricity demand (i.e. total demand from
industry, services, households and transportation), net
import (exogenous) and distribution losses. Electricity
can be produced by different technologies relying on
different energy sources - coal, oil, natural gas, nuclear
and renewables. The shares of electricity produced by
different fossil fuels are determined by the relative
costs of the different plants, which are a combination
of fuel costs and technology related costs. This in turn
determines demand for the different fuels, given fuel
efficiency in different plants. As in the transport model,
the fuel efficiency is based on the assumption of a
linear penetration of new technologies.
The fuel price module computes sectoral end user prices
for the different fuels. The end user prices are divided
into import prices, gross margins and taxes. For
electricity, the «import price» corresponds to the
electricity generation price calculated by the average
unit costs of producing electricity domestically. Gross
margins for all fuels include costs and profits in
transformation, distribution, retailing, etc. Taxes are
divided into fuel specific taxes, carbon taxes and a
value added tax.
2.3. Model input and output
Table 2.2 summarises the main SEEM model input and
output. The list reflects the menu for topics and policy
questions that the model user can study by simulating
SEEM.
Energy demand and emissions
Reports 96/12
Table 2.2. SEEM inputs and outputs
MODEL INPUT:
MODEL OUTPUT:
Cost variables
Fuel import prices
Fuel gross margins (costs and profits in transformation, distribution, retailing, etc.)
Fuel taxes (excise taxes, carbon taxes, VATs) Capital costs
Labour costs
Fuel demand
Coal
Oil products (light and heavy oil, gasoline, diesel, kerosene)
Natural gas
Electricity
Activity/income variables
GDP
Industry production
Services production
Private consumption
End user prices
For all fuels and sectors
Electricity generation costs
Technologies
Technologies in Transportation and Power generation (investment costs, fixed
and variable costs, efficiency, availability)
Autonomous energy saving in Industry, Services and Households
Net power import
Electricity production
Energy intensities
Total and by sector
Activity variables
Demand for kilometres
CO, emissions
Total and by fuel and sector
Fuel substitution possibilities
Demand sensitivity
11
Energy demand and emissions Reports 96/12
3. Integration or fragmentation? A brief
description of alternative economic
scenarios
In this section we describe the economic development
scenarios used as input to the SEEM model simulations,
starting with the integration scenario.
3.1. Ongoing Western European Integration
(IS)
This scenario is based on the assumption that the
ongoing European integration process will continue
more or less according to the time schedule in the
Maastricht treaty. Because of perceived positive economic perspectives we assume that the EU will be joined
by Switzerland and Norway around the turn of the
century. Hence, the integration process concerns all 13
Western European countries. Furthermore, we assume
an association of all Central and Eastern European
countries around year 2000, improving trade possibilities and access to foreign investments. In fact we
assume that all proposals mentioned in the Maastricht
Treaty are fully implemented by the year 2000. The
integration process will result in the completion of the
all objectives of the internal market, so free movement
of all goods, persons and capital will be realised.
We expect that the completion of the internal market
will have a moderate, but positive, overall effect on
economic productivity and income in EU. Funds for
structural improvements in the Southern European EU
countries presumably will contribute to a more equal
development pattern.
We expect that the European Monetary Union will
result in a single currency (ECU) and the establishment
of a Central bank before the year 2000. A stable
monetary situation without continuously changing
exchange rates will be reached at that time, increasing
economic prospects further.
Already political decisions in the field of environmental
protection, public health and consumers' protection are
made on Communal level. With respect to environmental policy, we assume more attention will be
given to «continental» issues, e.g. Eastern European
problems. Economic and social cohesion, high-tech
industry and research are subjects given high priority
by the Community. EU will co-ordinate these policies
Europe-wide with a minimum of national interference
and obstacles.
Of crucial importance to the issue analysed in this
report is that an energy tax harmonisation is assumed
to take place in the model countries. The tax is
harmonised towards the average tax levels presently
found in the four largest countries; Germany, France,
United Kingdom and Italy.
Table 3.1 summarises the main effects of continued
integration on some key variables.
Table 3.1. Assumed influence of further integration on some key factors in Western Europe (EU+EFTA) compared with present
situation
InteGDP
Ind.
Prod.
Em-
CompeEnergy
Labour
Trade
Interest
Pros- Innov
Environ
gration
pro-
cost
titive
ploy-
prices
perity
rate
ation
cost
ba-
ment
duction
strength
ment
lance
(EC)
ECWorld
-Internal
market
-Mone-
tary
-Social
-Political
++
++
++
++
+ +
0
0
+ +
0
0
++
0
0
++
0
0
++ significant positive effect (higher). + small positive effect (higher). 0 no clear effect. – small negative effect (lower).
— significant negative effect (lower).
12
++
++
0
++
Energy demand and emissions
Reports 96/12
No energy tax harmonisation is assumed to take place
in this scenario.
3.2. Western European Fragmentation (FS)
This scenario is based on the assumption that the EU
integration is halted from now on. National disagreements dominate further EU unification, resulting in a
more fragmented Western Europe.
The European Monetary Union will become a dead
letter and not realised. As a result of monetary
uncertainties, cross-country investments will decline
and international trade will stagnate and thus hamper
overall economic growth performance in all Western
European counties. A summary of the main effects of
fragmentation is given in table 3.2
Large innovative powers and competition mainly from the
Asian Pacific region will push Western Europe into a
relatively backward position. As a result, we assume that
overall average economic growth in Western Europe is
lower than in the integration scenario, and also results in
greater differences in growth between Western European
counties than in the integration scenario.
3.3. Model inputs
3.3.1. Economic growth
The above qualitative description of some possible
effects of integration or fragmentation in Europe on
economic growth is of course both brief and incomplete. It provides, however, some motivation for
the economic growth rates shown in table 3.3. In the
table, the average annual growth of GDP, production in
Industries and Services, and Private consumption are
shown. Together with information on energy prices
and autonomous technical change described in the
following subsections, this constitutes some of the key
input into the SEEM model.
Completion of the internal market will not progress
further. Instead increasing protectionism in specific
sensitive sectors such as agriculture, coal mining, gas
distribution, and electricity generation in many EUcountries might be expected. National intervention in
energy markets will prevail. Also permanent or even
increasing inequalities in the national taxation systems
will occur over the next decades. Some countries will
suffer more, however, from this halt in the integration
process, and see their economic growth declining more
than others. Particularly, we expect Finland, UK and
southern member states Italy and Spain to suffer most
in this situation.
Table 3.2. Assumed influence of fragmentation on some key factors in Western Europe (EU+EFTA) compared with present situation
EnvironInnova-
Pros-
Interest
Energy
Trade
Em-
Labour
Prod. Compe
FragmenGDP
Ind.
ment
perity
tion
prices
rate
batitive
ploy-
cost
tation
pro-
cost
lance
stren-
ment
ducti-
ECgth
on
World
(EC)
- Internal
market
- Mone++
tary
0
0
0
- Social
0
- Political
0
0
++ significant positive effect (higher). + small positive effect (higher). 0 no clear effect. - small negative effect (lower).
- significant negative effect (lower).
Table 3.3. Average annual growth in economic activity. 1991-2020. Per cent
Industry production
GDP
Services production
Private consumption
IS
FS
IS
FS
IS
FS
IS
FS
Austria
Belgium
Denmark
Finland
France
Germany
Italy
Netherlands
Norway
Spain
Sweden
Switzerland
United Kingdom
2.4
2.3
2.2
2.3
2.3
2.3
2.6
2.2
2.4
2.6
2.3
2.3
2.2
2.1
1.9
1.8
0.5
1.9
2.1
1.7
1.8
2.0
1.7
1.6
2.1
1.0
2.4
2.3
2.1
2.3
2.3
2.3
2.5
2.1
2.4
2.5
2.3
2.3
2.1
2.1
1.9
1.6
0.5
1.9
2.1
1.7
1.6
2.0
1.7
1.6
2.1
1.1
2.5
2.4
2.3
2.4
2.4
2.4
2.7
2.3
2.5
2.7
2.4
2.4
2.3
2.2
2.0
1.9
0.5
2.0
2.2
1.8
1.9
2.1
1.8
1.5
2.2
1.0
2.5
2.4
2.2
2.3
2.3
2.4
2.6
2.2
2.5
2.6
2.4
2.4
2.1
2.0
1.8
1.6
0.5
1.8
2.0
1.6
1.6
1.9
1.6
1.4
2.0
1.0
Average
2.3
1.7
2.3
1.7
2.4
1.8
2.4
1.6
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Reports 96/12
3.3.2. Energy prices
In the integration scenario we assume that a successful
economic transition in Russia will take place and that
this will keep oil and gas prices low. Together with the
structural developments in Western Europe this will
lead to decreasing gas prices. At about 2005 the gas
price is expected to be uncoupled from the oil price.
However in the fragmentation scenario, we assume a
monotonic, but modest, increase in oil and gas prices,
due to lack of new investments and thus exports from
Russia. After about 2015 the resulting gas prices reach
values above oil prices from the Middle East.
Figure 3.1 shows the development in oil and gas import
prices according to the two scenarios. We assume that
the coal import price for EU countries will remain
stable at the present price level in both scenarios.
Figure 3.1. Fossil fuel import prices. Average over SEEM
countries
1991 USD
per toe
- -
- -oil-is
gas-is
--A-- - oil-fs
gas-fs
240 -
coal
200 -
A -----A
160 120 80 40 0
1991
1995
2000
2005
2010
2015
3.3.3. Autonomous efficiency improvement
Our assumptions on autonomous efficiency improvement are rather conservative in both scenarios, due to
relative low prices in the integration scenario and a
lack of co-operation in the fragmentation scenario. In
general, efficiency improvement in IS is expected to be
larger than in FS, because of higher economic growth,
thus inducing faster turnover and more competition.
Furthermore, it is expected that industry is more
efficiency oriented, thus more improvement can be
realised here than in services or households.
In southern countries like Spain and Italy it is expected
that the starting situation lags behind Western European averages. Therefore, in these countries annually
realised efficiency improvements can be relatively higher, particularly in industry. Summarising, table 3.4
shows the country averages of the autonomous
efficiency improvements adopted in the simulations.
14
Table 3.4. Annual change in autonomous technical efficiency.
1991-2020. Per cent
IS
FS
Industry
Services
Households
0.6
0.3
0.4
0.2
0.4
0.2
Energy demand and emissions
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4. Simulation results
4.1. Energy demand
In the presentation of the simulation results, we first
concentrate on demand for the endogenously determined fossil fuels. Nuclear and renewable energy use
are mostly exogeneously given in the two scenarios.
The development in fossil fuel consumption can be
summarily explained by changes in:
• economic activity
• technological improvements
• fuel import prices
• fuel taxes
The relative impacts of these factors in going from the
integration (IS) to the fragmentation (FS) scenario is
shown in table 4.1.
Table 4.1. Impacts on energy consumption of various factors in
going from IS to FS
Economic growth
Technology
Fuel import prices
Fuel tax harmonisation
Oil
Gas
_
_
+
_
+
_
+
—
Coal
Total
0
0
Total
(+ indicates higher fuel demand in FS than in IS)
Since we have assumed a higher economic activity
growth in IS than in FS (approximately 2.3 per cent per
year vs. 1.7 per cent), this tends to lower the demand
for all fuels in FS compared to IS. This is marked by
in the table. The technology assumptions work the
opposite way. We have assumed higher (autonomous)
energy savings and fuel efficiency improvements in the
integration scenario (see table 3.4), implying that, at
constant fuel prices, the energy intensity will become
higher in FS, i.e. more fuel is used per output ("+" in
the table). Roughly speaking, the activity effect and the
technology effect tend to more or less offset each other
when it comes to the overall effect on total fuel
demand.
From figure 3.1 it is clear that the oil and gas prices are
lower in the integration scenario than in the fragmentation scenario, resulting in lower oil and gas
consumption in FS than in IS. The price differences are
especially high for oil from 2005, so the effects have
time to work out completely despite lag effects in the
model. This results in a double "—" for the oil demand
difference between FS and IS in the table. Although the
coal import price stays constant in both scenarios, it is
more favourable compared to oil and gas prices in the
FS scenario. Thus, the fuel price effect is that coal
demand is higher in FS than in IS.
The fourth major difference in input between the
scenarios is the tax harmonisation implemented in the
integration scenario. Due to extremely high taxes on
natural gas used in households in some countries
where gas consumption is high (Italy is the main
example), removal of the harmonisation leads to
reduced gas consumption at the aggregate level. The
effect on oil is opposite (but weak), mainly because
some of the large countries today have gasoline taxes
slightly below the average of the four big countries.
Overall, the effect of the tax harmonisation must be
considered to be weak.
Summing up the separate effects, as shown by the
bottom line of the table, the net effect of the different
scenario inputs is that the demand for oil, gas and total
energy demand, is higher in the IS scenario than in the
FS scenario. Altered input assumptions could of course
change these results. For instance, a higher rate of
technology improvement in the integration scenario
would reduce the gap between total fuel demand in IS
and FS.
The figures 4.1 - 4.3 show the simulated time paths of
aggregated demand for natural gas, oil and coal in the
integration (IS) and fragmentation scenarios.
15
Energy demand and emissions Reports 96/12
Figure 4.1. Demand for gas. Thousand tonnes oil
equivalents (ktoe)
demand drops in the fragmentation scenario relative to
the integration scenario, less investments are made in
thermal power supply, postponing the introduction of
gas fired power plants.
ktoe
800,000, 700,000 600,000 500,000 400,000 300,000 200,000:
Table 4.2. Average annual growth in energy demand 19912020. Per cent
Gas
Oil
Coal
Total
2.1
1.2
1.0
1.1
1.8
1.1
100,000 11111111111111111111111-1111
1991
1997
2003
2009
2015
1111111111111
2003
2009
2015
Figure 4.3. Demand for coal. Thousand tonnes oil
equivalents (ktoe)
ktoe
800,000 700,000 600,000 500,000 400,000 300,000 -
IS
200,000 -
- FS
100,000 0
1991
-
1
111
1
1997
2003
2009
2015
From the figures and table 4.2 below, we note that in
the integration scenario oil demand is expected to
show the fastest growth, closely followed by gas. Coal
demand show only half the growth rate of the two
other fossil fuels. In considering the effects of fragmentation, we note a reduction in the growth rate of
oil and gas of almost 1 percentage point, while demand
for coal actually increases slightly. The explanation for
this is that under the adverse economic conditions in
the fragmentation scenario and without a deregulation
of the national coal industries, the coal price is competitive with the other fuels. Also, since electricity
16
1.9
1.1
Total fossil fuel demand shows an average annual
growth in the integration scenario of 1.8 per cent. In
the fragmentation scenario the growth rate is 1.1 per
cent. Thus, fossil fuel demand growth is lower than the
economic growth in both scenarios, but energy use is
reduced relatively more than economic activity in going
from the integration to the fragmentation scenario.
Table 4.3 shows the fossil energy demand by countries
in the base year (1991) and annual average growth
over the period 1991 - 2020 in the integration and
fragmentation scenarios.
Figure 4.2. Demand for oil. Thousand tonnes oil
equivalents (ktoe)
ktoe
800,000 IS
700,000 - FS
600,000 500,000 400,000 300,000 200,000 100,000 0 -
1991
1997
IS
FS
We note that the demand for fossil fuels grows faster in
the southern countries, Italy in particular, than in most
of the other countries in the integration scenario. The
south, together with Finland, are also hardest hit (i.e.
show the largest reductions in energy use) by
fragmentation.
Germany, Italy, United Kingdom, the Netherlands and
France are the main countries with respect to demand
for gas. Their shares of demand in 1991 range from 23
per cent for Germany down to 12 per cent for France.
Oil demand is also dominated by the four large countries (demand shares varying from 24 per cent for Germany to 15 per cent for United Kingdom), while coal
demand is dominated by two countries only; Germany
with a demand share of 42 per cent in 1991 and United
Kingdom with a share of 24 per cent.
In the integration scenario Italy and France show
growth in demand for gas above the average growth
rate, while Germany, United Kingdom and the Netherlands have growth rates well below the average. The
same pattern is also found in the fragmentation scenario, but here the spread between the highest and
lowest growth rates is much narrower.
With respect to oil, we find in the integration scenario
that demand in Italy again is expected to be well above
the average at 2.1 per cent per year, while Germany
and United Kindom have growth rates well below the
average. Turning to the fragmentation scenario, we
find that oil demand in Germany and France are just
sligthly reduced, giving them growth rates above the
Energy demand and emissions
Reports 96/12
Table 4.3. Fossil fuel demand in 1991 (ktoe) and average annual growth rates 1991-2020
1991 (ktoe)
Country'
AU
BE
BR
CH
DK
FR
GB
IT
NL
NO
SF
SP
SW
Total
Annual average growth
1 991 -2020 IS (Per cent)
Annual average growth
1 991 -2020 FS (Per cent)
Gas
Oil
Coal
Gas
Oil
Coal
Gas
Oil
Coal
5,096
8,430
49,959
2,038
1,512
26,396
41,615
47,352
30,248
2,352
4,833
507
9,545
15,188
104,365
12,628
7,340
68,025
65,458
73,505
12,433
8,060
8,600
37,456
10,962
4,299
9,584
112,695
722
7,687
19,286
64,834
14,654
8,370
854
5,983
19,144
2,745
2.1
1.4
1.4
1.5
1.0
2.1
1.4
2.7
1.6
1.6
1.0
0.9
1.0
1.5
1.7
0.8
1.5
0.7
1.3
1.1
1.2
2.1
1.6
0.8
1.0
1.4
0.4
1.6
0.4
1.5
1.1
1.4
1.2
1.2
2.1
0.7
1.4
1.7
1.8
1.9
1.3
3.5
1.4
1.8
0.9
2.9
2.5
-0.2
0.6
0.6
1.8
0.6
1.3
1.6
0.9
1.4
0.2
1.5
0.9
1.3
-0.1
1.4
1.0
1.8
1.2
1.1
1.2
1.0
1.7
0.7
1.9
1.0
1.5
0.2
0.8
0.9
220,338
433,566
270,856
1.9
2.1
1.0
1.1
1.2
1.1
a) Country codes are explained in table 2.1.
average level, now at 1.2 per cent annually. Although
oil demand in Italy is reduced considerably from the
integration scenario, the growth in demand here is still
above the average level. Demand for oil in United Kingdom is reduced to a very small growth rate of only 0.2
per cent per year on average.
the integration scenario. Coal reduces its share correspondingly from almost 1/3 to almost 1/4• In the fragmentation scenario the shares in year 2020 are equal to
the shares prevalent in 1991.
Table 4.4. Fuel shares in total demand for fossil fuels
in 1991and 2020. Per cent
The growth in total demand for coal is dominated by
the development in Germany and UK, which both show
growth of almost 1 per cent per year in the integration
scenario. In going to the fragmentation scenario, the
growth rate in Germany increases slightly due to
slower replacement of older power plants, while the
growth is marginally reduced in UK.
Gas
24
25
24
1991
IS-2020
FS-2020
Oil
Coal
47
51
47
29
24
29
The sectoral demand for fossil fuels shown in table 4.5
indicates that the growth rates are more equal across
sectors than across fuel types or countries, cf. table 4.3.
However, with an annual average growth rate in total
demand of approximately 2 per cent, we find that
energy use for transportation and household demand
for fossil fuels in the integration scenario grow some-
Table 4.4 shows the fossil fuel shares in 1991 and 2020
in the integration and fragmentation scenarios. We
note that the share of gas in total fossil fuel demand is
almost constant at 1/4 both in 1991 and in 2020 (both
scenarios). Oil increases its share from somewhat
below 1/2 to somewhat above 1/2 from 1991 to 2020 in
Table 4.5. Demand for fossil fuels by sector in 1991 (ktoe) and average annual growth in the integration and fragmentation
scenarios over the period 1991-2020
Sector'
Annual average growth
1 991 -2020 FS (per cent)
Annual average growth
1 991 -2020 IS (per cent)
1991 (ktoe)
Gas
Oil
Coal
Gas
Oil
Coal
Gas
Oil
Coal
EL
HO
IN
SE
ST
FC
MO
35,938
84,435
69,307
26,769
216,449
180,511
3,889
46,980
56,091
49,363
40,093
192,527
145,546
241,040
197,153
14,236
55,539
3,928
270,856
73,703
1.6
2.2
1.4
1.9
1.8
1.9
2.3
3.2
1.6
2.0
1.2
2.1
1.9
2.1
0.9
1.7
1.2
3.0
1.0
1.4
1.2
1.2
0.6
1.6
1.1
1.1
1.2
1.0
0.8
0.0
1.3
0.8
1.2
1.4
1.0
1.1
1.1
2.5
1.1
1.2
Total
220,338
433,567
270,856
1.9
2.1
1.0
1.1
1.2
1.1
Sector codes are explained in table 2.1.
17
Reports 96/12
Energy demand and emissions
what faster than demand from the other sectors. In
comparison, industry shows a growth rate of 1.5 per
cent. In the fragmentation scenario we note that demand from the service sector remains relatively unaffected by the scenario assumptions, and displays only
a slight decrease relative to the integration scenario.
The difference in oil demand between IS and FS is
largest in the electricity generation sector. This is
mainly explained by the low taxes in the integration
scenario, and thus heavily decreasing prices in the
electricity sector. Furthermore, especially in the UK and
Italy, a major difference between activity growth is
assumed, resulting in a large demand for electricity in
IS.
The gap in oil demand in the industry sector between
IS and FS is also rather large. This can be explained by
low tax rates combined with relatively high elasticities.
For sectoral gas demand the services sector shows only
a small difference between IS and FS. This is due to
high taxes which dampen the differences in gas import
prices between the two scenarios. In the household
sector the tax rates are also relatively high. However,
reaction on energy demand is much larger, because
income elasticities in that sector are much greater than
in the service sector.
The sectoral demand for coal is dominated by the
electricity generating sector. In contrast to the other
fuels, demand for coal is slightly increased in going
from the integration to the fragmentation scenario. As
mentioned before, this is mainly due to a slower
replacement of old coal fired power plants in the
fragmentation scenario.
4.2. Emissions to air
its share of emissions, while Italy increases its share. In
the fragmentation scenario the 1991-shares are more
or less restored in 2020, expect for United Kingdom
which reduces its share from 19 per cent to 16 per cent
in both scenarios.
With respect to type of fuel, we find that the share of
oil related emissions, and to a much smaller extend the
gas related emissions, increase in the integration scenario, while the base year shares are restored in the
fragmentation scenario in 2020.
Electricity generation and transport are the dominating
sectors with respect to CO, emissions. Since transport
activities are assumed to grow relatively fast in both
scenarios, its share increases from 26 per cent in 1991
to 29 per cent in year 2020 in the integration scenario
and 28 per cent in the fragmentation scenario. Electricity generation reduces its share from 34 per cent in
1991 to 31 and 33 per cent in year 2020 in the IS and
FS scenarios, respectively.
Figure 4.4. Emissions of CO, by group of countries
Mill.
tonnes
5000 -
0
4000 -
South
1111Nordic
CI Small
0 United Kingdom
3000 2000 -
0
1000 -
France
• Germany
0
1991
IS-
2020
FS2020
Figure 4.5. Emissions of CO, by type of fuels
4.2.1. Emission of CO2
Emissions of CO, are determined by the carbon content
of each fuel. The emission factors employed in this
study are as follows: Gaseous fuels: 2.4, liquid fuels:
3.1 and solid fuels: 3.9, all measured in (metric) tonnes
of CO, per tonnes oil equivalents (t.o.e.). Figures 4.4 4.6 show emission levels in 1991 and in year 2020 in
the two scenarios from groups of countries6, by fuel
types and by sectors. Average annual growth in CO,
emissions are 1.7 per cent in the integration scenario
and 1.1 per cent in the fragmentation scenario. Total
CO, emissions grow somewhat slower than total demand for fossil fuels, since both oil and gas (with
relatively low emission coefficients) grow faster than
demand for coal (with a relatively high emission coefficient). In the integration scenario Germany reduces
6
The country aggregates are defined by the following labels:
Austria, Switzerland, Belgium and the Netherlands are the «Small.
countries. The “South” countries consist of Italy and Spain, while
the «Nordic» countries are Denmark, Finland, Sweden and Norway.
18
Mill.
tonnes
5000 -
El Coal
Oil
M Gas
4000 '3000
2000 1000 0
1991
IS-2020
FS-2020
Energy demand and emissions
Reports 96/12
Figure 4.7. SO2 emissions in 1991 and 2020 by country groups
Figure 4.6. Emissions of CO, by sectors
Mill. tonnes
Mill. tonnes
SO2
5000 4500 4000 3500 3000 2500 2000 1500 1000 500 0
O M°
• SE
M IN
0 HO
• EL
South
• Nordic
0
IN Small
0 United Kingdom
0 France
• Germany
0
1991
1991
IS-2020
FS-2020
4.2.2. Emissions of SO2 and NO
Unlike CO, emissions, the emission of SO2 and NO
depends on how the fossil fuels are burned (combustion technology) as well as the amount of cleaning of
exhaust gases that takes place. These emissions will
therefore not necessarily follow the pattern of fossil
fuel demand. Also, in the case of sulphur emissions,
these are dominated by the demand for coal which is
more sulphurous than the other fossil fuels.
As mentioned above, we calculate the emissions of SO2
an NO by inserting energy trajectories from the SEEM
model into IIASA's RAINS model (Alcamo et al. 1990,
Kolsrud, 1996). The simulated SEEM figures are suitably transformed to take into account differences in
definitions of sectors and fuels between the two models. Utilising the technology assumptions incorporated
in the Official Energy Pathway (OEP) scenario of
RAINS, we can then calculate SO2 and NO emissions
and also use the atmospheric transport module to find
the deposition pattern associated with our energy
scenarios'.
Total SO2 emissions are growing at an annual average
rate of 1.3 per cent in the integration scenario versus
only 0.5 per cent in the fragmentation scenario, see
figure 4.7. These comparatively low growth rates are
due to the fact that SO2 emissions from Germany are
declining in both scenarios. This is explained by the
forecasted large reduction in coal used in the eastern
7
35 30 25 20 15 10 5-
As explained in Alfsen et al. (1995) and Kolsrud (1996), SEEM
does not provide values for all the energy variables entering the
RAINS model. In addition, the Official Energy Pathway scenario of
the RAINS model, that provides the technology parameters relevant
to the SO2 and NO emission calculations, has a time horizon to year
2000. After this time, we have kept the technology parameters
constant in our simulations. This allows us to study the partial
effects of changing energy consumption pattern, and to interpret the
results in purely economic terms. Furthermore, the energy variables
not provided by SEEM are forecasted using total demand for solid,
liquid and gaseous fossil fuels simulated by SEEM as relevant
indicators.
IS-
2020
FS2020
Figure 4.8 NO, emissions in 1991 and 2020 by country groups
Mill. tonnes
N O2
30 25 20
OSouth
15 -
• Nordic
10 -
El Small
CI United Kingdom
5-
El France
Germany
0
1991
I5-2020
FS-2020
part of the country. The other big contributer to SO2
emissions is the southern block, i.e. Italy and Spain.
High economic growth rates in the integration scenario
lead to high emissions. In 2020 their combined emission share is almost 40 per cent, up from 28 per cent in
the base year 1991. Even in the fragmentation scenario, where their economic growth is closer to the average growth of all countries, Italy and Spain increase
their share of SO2 emissions from 28 per cent to 32 per
cent.
Total NO emissions grow more in line with total energy demand, see figure 4.8. While SO, emissions were
determined by the use of coal and oil primarily in the
power producing sector, transport oil use is an important determinant for the NO emissions. The southern
countries also in this case increase their shares of emissions from 20 per cent in 1991 to 30 per cent in 2020
in the integration scenario and more modestly to 23
per cent in the fragmentation scenario.
Further information on the SO2 and NO emissions are
given in the tables 4.6 and 4.7. Both oil and coal use
contribute significantly to the SO2 emissions. The coal
use is not much affected by neither integration nor
19
Reports 96/12
Energy demand and emissions fragmentation, and coal emissions grow in both scenarios at a modest average rate close to 0.1 per cent per
year. Oil contributes more to SO2 and NO emissions in
the future than in 1991 in both scenarios, but most
prominently in the integration scenario. From table 4.7
we note that most of the SO2 emissions are coming
from the power producing sector, and that this is the
case also in the future in both scenarios although other
sectors' contribution are likely to grow somewhat.
Table 4.6. Shares om emissions in 1991 and average annual
growth rates from 1991 to 2020 in the integration
(IS) and the fragmentation (FS) scenarios by fuel
type. Per cent
Average annual
growth
1991-2020
FS
IS
SO2
, emissions
Shares
1991
Gas
Oil
Coal
Othera
Total
Average annual
growth
1 991 -2020
IS
FS
NO
emissions
Shares
1991
36
61
4
2.9
0.1
0.2
1.0
0.2
0.0
5
71
20
3
1.7
2.2
0.7
-0.1
1.0
1.4
0.8
-0.1
100
1.3
0.5
100
1.7
1.2
Other includes emissions from non-combustion processes and from use of
alternative technologies.
in the SEEM countries coming from the SEEM countries. Table 4.8 shows the average annual growth rates.
The figures 4.9 and 4.10 show the deposition of oxidised sulphur and nitrogen in groups of SEEM countries coming from these same groups in 1991 and in
2020.
Table 4.8. Average annual growth rates in deposition of
oxidised sulphur and nitrogen. 1991-2020. Per cent
IS
FS
SO2
emissions.
Shares
1991
Conversion
Power
prod.
Domestic
Traffic
Industry
Total
Average annual
growth
1991-2020
FS
IS
NO
emissions.
Shares
1991
Average
annual growth
1991-2020
IS
FS
2.9
1.2
2
2.3
1.2
68
10
3
11
1.0
1.4
2.6
1.7
0.4
0.4
1.6
0.3
21
5
65
6
1.1
1.8
2.1
1.5
0.7
1.1
1.5
0.7
100
1.3
0.5
100
1.7
1.2
Deposition of sulphur and oxidised nitrogen is calculated using the above emission figures and the transport matrices for 1991, as given by Sandnes (1993).
The SEEM countries only constitute a subset of the
countries covered by RAINS and the transport matrices.
Here we only consider the contribution to depositions
20
1.8
1.2
SO2
20 O South
• Nordic
0 Small
5 -
VX,1
rOM
United Kingdom
0 France
• Germany
1991
I5-2020
FS-2020
Figure 4.10 Nitrogen deposition in 1991 and 2020
Mill. tonnes
NO2
O South
M Nordic
III Small
8
4.2.3. Deposition of SO2 and NOR-
1.4
0.5
Mill. tonnes
10 -
Table 4.7 Shares om emissions in 1991 and average annual
growth rates from 1991 to 2020 in the integration
(IS) and the fragmentation (FS) scenarios by RAINS'
sectors. Per cent
NO
Figure 4.9 Sulphur deposition in 1991 and 2020
15 -
The use of oil is the most prominent cause of NO emissions in the SEEM countries, in particular for transport
purposes. The dominant role of transport is likely to increase in the future.
SO2
• United Kingdom
0 France
• Germany
Table 4.9 show how the ratio between depositions and
emissions develop from 1991 to 2020 in the two
scenarios.
Reports 96/12
Energy demand and emissions
Table 4.9 The ratio between deposition and emission of
oxidised sulphur and nitrogen in the integration (IS)
and fragmentation (FS) scenario by country groups
NO2
SO,
I5-2020 FS-2020
1991
15-2020
FS-2020
1991
Germany
France
United
Kingdom
Small
Nordic
South
0.48
0.87
0.54
0.77
0.51
0.76
0.37
0.58
0.40
0.57
0.38
0.54
0.40
0.86
0.84
0.52
0.39
0.83
0.74
0.50
0.40
0.77
0.81
0.51
0.19
0.57
0.95
0.47
0.21
0.60
0.86
0.42
0.21
0.55
0.93
0.46
Total
0.54
0.55
0.55
0.45
0.46
0.46
Overall, we find the ratios of deposition to emission to
be larger for sulphur than for nitrogen with relatively
more of the sulphur emissions being deposited in the
SEEM countries. France, the small countries in central
Europe and the Nordic countries receive more than 80
per cent of the amounts they emit. At the opposite end
of the scale we find that United Kingdom, Germany
and the southern countries of Italy and Spain receive
about half or less of what they emit. With regards to
nitrogen, the Nordic countries receive the most relative
to their own emissions, while United Kingdom is the
largest contributor to depositions in other SEEM countries.
In the integration scenario we find that Germany receives relatively more SO2 compared to its emissions,
while the opposite is the case for France and the Nordic
countries. Only small changes in the deposition/emission ratios are experienced by the other country
groups. With respect to nitrogen, the most prominent
changes over time in the integration scenario are the
reductions in relative depositions in both southern and
Nordic countries.
Going from the integration to the fragmentation
scenario, we find a decline in the relative deposition of
both sulphur and nitrogen in the small country group,
while the relative deposition increases in the Nordic
group.
21
Energy demand and emissions Reports 96/12
5. Conclusion
Several models in the literature have analysed energy
scenarios for Western Europe, e.g. Global 2100 (Manne
and Richels, 1992), GREEN (Bumiaux et al., 1992) and
ECON-ENERGY (Haugland et al., 1992). However, in
these models Western Europe is treated as one block.
In contrast, the SEEM model is more detailed, since it
models energy demand and emissions to air from each
of the countries covered. The SEEM model is also
unique in that it allows for a linkage to the RAINS
modelling system.
The SEEM simulations in this paper have been based
on two exogenously given economic growth scenarios
with the following main features:
• The economy shows only modest growth in the integration scenario, strongest in the southern part of
Europe. The growth rate is even lower in the
fragmentation scenario. The southern countries
experience the largest reduction in economic
growth, while the growth in Germany is almost
unaffected in going from the integration to the
fragmentation scenario.
With respect to the issues addressed in this paper, i.e.
the effect of integration or fragmentation in Europe on
future energy demand, emissions to air and deposition
of acid compounds, the simulations indicate that:
• Overall the demand for fossil fuels grows at an average annual rate of 1.8 per cent in the integration
scenario and 1.1 per cent in the fragmentation scenario. Average annual growth in demand for oil and
gas in the integration scenario is around 2 per cent
per year, while demand for coal grows at a rate
close to 1 per cent per year. In the fragmentation
scenario the demand for coal is slightly higher,
while the average annual growth in demand for oil
and gas is reduced to approximately 1 per cent.
22
• Growth in CO, emissions follows the growth in
overall demand for fossil fuels. The power generating sector and transport are the two most contributors to CO, emissions, each with an emission
share of around 30 per cent.
• SO, emissions are dominated by oil and coal use in
the power generating sector. Italy, United Kingdom
and Germany are the largest contributers. The
average annual growth in total 502 emissions in the
integration and the fragmentation scenarios are 1.3
and 0.5 per cent, respectively. The stronger growth
in the integration scenario is due to higher demand
for oil.
• NO emissions are more evenly distributed among
the countries, and is strongly dominated by
emissions from transportation. This is also the
sector with the strongest economic growth. Overall
we find that the average annual growth in NO
emissions are close to the growth in demand for
fossil fuels and CO, emissions, i.e. 1.7 and 1.2 per
cent in the integration and the fragmentation
scenario, respectively.
• With regard to depositions of 502 and NO., they
follow the emission pattern quite closely, with slow
or no growth in sulphur deposition in Germany and
relatively high growth in the southern countries.
Growth in nitrogen depositions are more evenly
distributed among the countries.
With respect to further work, we would like to point
out the following. The data used for estimating and
calibrating elasticities and other parameters in the
model can always be improved. Furthermore, the
model's treatment of energy trade is simplistic. Finally,
being a partial energy model, SEEM lacks explicit
modelling of the linkages to economic growth. Further
work in all of these areas could improve the ability of
the model apparatus to address the many future
challenges facing EU and neighbouring countries in
Europe in the years ahead.
Reports 96/12
Energy demand and emissions
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Oslo.
Boug, P. (1995): User's Guide. The SEEM model
version 2.0, Documents 95/6, Statistics Norway, Oslo.
Boug, P., and L. Brubakk (1996): Impacts of economic
integration on energy demand and CO, emissions in
Wester Europe, to appear in the series Discussion
papers, Statistics Norway, Oslo.
Brubakk, L., M. Aaserud, W. Pellekaan and F. van
Oostvoorn (1995): SEEM - An energy demand model
for Western Europe, Reports 95/24, Statistics Norway,
Oslo.
Burniaux, J. M., J. P. Martin, G. Nicoletti and J.
Oliviera Martins (1992): GREEN - A multi-region
dynamic general equilibrium model for quantifying the
costs of curbing CO, emissions: A technical manual,
Working Paper 116, OECD Economics Department,
Paris.
Haugland, T., 0. Olsen and K. Roland (1992):
Stabilizing CO, emissions: Are carbon taxes a viable
option?, Energy Policy 20, 405-419.
TEA (International Energy Agency) (1993a): Energy
balances in the OECD countries. 1960-1991, IEA, Paris.
23
Energy demand and emissions
Reports 96/12
Appendix: Country tables
Table A.1 Emissions of SO2, NO and COP. Level in 1991 and per cent average annual growth 1991-2020 in the integration (IS) and
fragmentation (FS) scenarios
Emissions
kt SO2
Average annual growth
1 991 -2020
kt NO2
Average annual growth
1 991 -2020
1991
IS
Austria
348
2.0
Belgium
538
1.0
Denmark
334
1.7
0.8
284
1.6
Finland
506
1.1
0.3
312
1.0
FS
Mt CO,
Average annual growth
1991-2020
1991
IS
1.8
332
2.1
2.0
59
2.0
1.8
0.6
480
1.0
1.0
105
1.0
0.9
1.0
56
1.6
0.9
0.1
56
1.0
0.0
FS
1991
IS
FS.
France
1,641
2.4
1.5
2,089
1.9
1.6
349
1.9
1.5
Germany
8,225
-0.4
-0.4
4,579
1.0
1.0
883
1.2
1.1
Italy
3,761
3.4
1.6
1,737
3.2
1.7
399
3.1
1.6
393
1.5
0.9
639
1.3
1.0
144
1.3
1.0
90
0.6
0.4
287
2.1
1.9
28
1.7
1.3
2,563
0.7
-0.2
1,359
2.9
1.5
202
2.2
1.1
311
2.1
0.3
325
2.0
1.1
46
2.4
1.0
79
1.2
1.1
242
1.8
1.8
47
1.6
1.6
4,132
1.3
0.6
2,728
0.9
0.3
556
1.1
0.5
22,921
1.3
0.5
15,393
1.7
1.2
2,929
1.7
1.1
Netherlands
Norway
Spain
Sweden
Switzerland
United Kingdom
Total
Table Al Deposition of SO2 and NOR. Thousand tonnes in 1991 and per cent average annual growth 1991-2020 in the integration
(IS) and fragmentation (FS) scenarios
Deposition
kt SO,
Average annual growth 1 991 -2020
1991
IS
Austria
502
Belgium
279
Denmark
kt NO,
Average annual growth 1 991 -2020
FS
1991
IS
FS
1.6
1.0
414
1.9
1.4
1.2
0.8
140
1.4
1.1
151
1.0
0.5
100
1.2
0.9
Finland
319
1.0
0.2
245
1.3
0.8
France
1,482
1.9
1.1
1,230
1.9
1.4
Germany
6,463
0.8
0.7
1,677
1.4
1.2
Italy
1,876
3.2
1.4
844
2.6
1.6
Netherlands
321
1.2
0.8
181
1.3
1.0
Norway
230
0.9
0.4
337
1.3
1.0
1,378
0.8
-0.1
696
2.7
1.5
Sweden
380
1.2
0.3
458
1.4
1.0
Switzerland
268
2.1
1.1
231
2.0
1.5
1,639
1.3
0.6
526
1.1
0.7
15,286
1.4
0.8
7,078
1.8
1.2
Spain
United Kingdom
Sum
24
Reports 96/12
Energy demand and emissions
Tidligere utgitt pa emneomrficiet
Previously issued on the subject
Documents
95/6 P. Boug: User's Guide. The SEEM-model Version
2.0.
96/1 D. Kolsrud: Documentation of Computer
Programs that Extend the SEEM Model and
Provide a Link to the RAINS Model
Rapporter (RAPP)
95/24 L. Brubakk, M. Aaserud, W. Pellekaan og F. van
Oostvoorn: An Energy Demand Model for
Western Europe
Okonomiske analyser (OA)
8/94 K.H. Alfsen og M. Aaserud: Klimapolitkk,
kraftproduksjon og sur nedbor. Noen
simuleringsresultater fra den flersektorelle
europeiske energimodellen SEEM
Economic Survey (ES)
3/93 H. Birkelund, E. Gjelsvik og M. Aaserud: Effects
of an EC Carbon/Energy Tax in a Distorted
Energy Market
Discussion Papers (DP)
81
H. Birkelund, E. Gjelsvik and M. Aaserud:
Carbon/Energy Tax and the Energy Market in
Western Europe
104 K.H. Alfsen, H. Birkelund and M. Aaserud:
Secondary Benefits of the EC Carbon/Energy
Tax
25
Energy demand and emissions Reports 96/12
De sist utgitte publikasjonene i serien Rapporter
Recent publications in the series Reports
95/20 R.H. Kitterod: Tid nok, - men hva sa? Tidsbruk
og tidsopplevelse blant langtids-arbeidsledige.
1995. 123s. 110 kr. ISBN 82-537-4177-4
95/33 T.A. Johnsen og B.M. Larsen: Kraftmarkedsmodell med energi- og effektdimensjon. 1995.
54s. 95 kr. ISBN 82-537-4212-6
95/21 N. Keilman and H. Brunborg: Household
Projections for Norway, 1990-2020 Part I:
Macrosimulations. 1995. 82s. 95 kr. ISBN 82537-4178-2
95/34 F. R. Aune: Virkninger pa de nordiske energimarkedene av en svensk kjemekraftutfasing.
1995. 58s. 95 kr. ISBN 82-537-4213-4
95/22 R.H. Kitterod: Tidsbruk og arbeidsdeling blant
norske og svenske foreldre. 1995. 100s. 110 kr.
ISBN 82-537-4179-0
95/23 H. Rudlang: Bruk av edb i skolen 1995. 1995.
77s. 95 kr. ISBN 82-537-4181-2
95/24 L. Brubakk, M. Aaserud, W. Pellekaan and
F. van Oostvoom: SEEM - An Energy Demand
Model for Western Europe. 1995. 66s. 95 kr.
ISBN 82-537-4185-5
95/25 H. Luras: Framskriving av miljoindikatorer.
1995. 30s. 80 kr. ISBN 82-537-4186-3
95/26 G. Frengen, F. Foyn and R. Ragnarson: Innovation in Norwegian Manufacturing and Oil
Extraction in 1992. 1995. 93s. 95 kr. ISBN 82537-4189-8
95/27 K.H. Alfsen, B.M. Larsen og H. Vennemo:
Bwrekraftig Økonomi? Noen alternative
modellscenarier for Norge mot ar 2030. 1995.
62s. 95 kr. ISBN 82-537-4190-1
95/28 L.S. Storni*: Flytting og arbeidsstyrken:
Flyttetilboyelighet og flyttemonster hos
arbeidsledige og sysselsatte i perioden 19881993. 1995. 66s. 95 kr. ISBN 82-537-4193-6
95/29 G. Dahl, E. Flittig, J. Lajord og D. Fredriksen:
Trygd og velferd. 1995. 91s. 95 kr. ISBN 82537-4198-7
95/30 T. Skjerpen: Seasonal Adjustment of First Time
Registered New Passenger Cars in Norway by
Structural Time Series Analysis. 1995. 35s. 80
kr. ISBN 82-537-4200-2
95/31 A. Bnivoll og K. Ibenholt: Norske avfallsmengder etter artusenskiftet. 1995. 41s. 80 kr.
ISBN 82-537-4208-8
95/32 S. Blom: Innvandrere og bokonsentrasjon i Oslo.
1995. 125s. 95 kr. ISBN 82-537-4211-8
26
95/35 M.S. Bjerkseth: Engroshandelen i Norge 19851992. 1995. 43s. 95 kr. ISBN 82-537-4214-2
95/36 T. Komstad: Vridninger i lonnstakemes relative
brukerpriser pa bolig, ikke-varige goder og fritid
1985/86 til 1992/93. 1995. 35s. 80 kr. ISBN 82537-4216-9
95/38 G.J. Limperopoulos: Usikkerhet i oljeprosjekter.
1995. 72s. 95 kr. ISBN 82-537-4222-3
96/1 E. Bowitz, N.O. Mwhle, V.S. Sasmitawidjaja and
S.B. Widoyono: MEMLI - The Indonesian Model
for Environmental Analysis: Technical
Documentation. 1996. 70s. 95 kr. ISBN 82-5374223-1
96/2 A. Essilfie: Investeringer, kostnader og gebyrer i
den kommunale avlopssektoren: Resultater fra
undersokelsen i 1995. 1996. 36s. 80 kr. ISBN
82-537-4239-8
96/3 Resultatkontroll jordbruk 1996: Gjennomforing
av tiltak mot forurensninger. 1996. 85s. 95 kr.
ISBN 82-537-4244-4
96/4
A. Osmunddalen og T. Kalve: Bofaste
innvandreres bruk av sosialhjelp 1987-1993.
1996. 33s. 80 kr. ISBN 82-537-4245-2
96/5 S. Blom: Inn i samfunnet? Flyktningkull i
arbeid, utdanning og pa sosialhjelp. 1996. 84s.
95 kr. ISBN 82-537-4249-5
96/6 J.E. Finnvold: Kommunale helsetilbud:
Organisering, ulikhet og kontinuitet. 1996. 70s.
95 kr. ISBN 82-537-4221-5
96/8 K.E. Rosendahl: Helseeffekter av luftforurensning og virkninger pg okonomisk
aktivitet: Generelle relasjoner med anvendelse
pa Oslo. 1996. 40s. 80 kr. ISBN 82-537-4277-0
96/12 K.H. Alfsen, P. Boug and D. Kolsrud: Energy
demand, carbon emissions and acid rain.
Consequences of a changing Western Europe.
1996. 26s. 80 kr. ISBN 82-537-4285-1
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